Best Researcher Award
| Researcher Information | |
|---|---|
| Affiliation | Daffodil International University |
| Country | Bangladesh |
| Scopus ID | THiIDGIAAAAJ |
| Documents | 3 |
| Subject Area | Artificial Intelligence, Medical Imaging, Computer Science |
| Event | Young Research Excellence Award |
| ORCID | 0009-0006-6164-1620 |
Tamim Mahmud is a final-year Computer Science and Engineering student at Daffodil International University, Bangladesh. His academic work focuses on artificial intelligence, machine learning, deep learning, computer vision, and medical image analysis. Through multiple research appointments and collaborative projects, he has contributed to AI-assisted healthcare technologies, explainable artificial intelligence, uncertainty-aware deep learning, and intelligent diagnostic systems.[1]
Contents
Abstract
Tamim Mahmud has established an emerging research profile in artificial intelligence for healthcare through work in medical imaging, disease prediction, explainable AI, and uncertainty-aware deep learning. His publications and ongoing research projects emphasize clinically relevant computer vision models, diagnostic decision support, and robust machine learning methodologies. His contributions demonstrate interdisciplinary integration between computer science and medical research.[2]
Keywords
Artificial Intelligence, Computer Vision, Deep Learning, Medical Imaging, Machine Learning, Explainable AI, Healthcare Informatics, Disease Prediction, MRI Analysis, CT Imaging.
Introduction
Mahmud’s research centers on developing intelligent healthcare systems capable of improving disease diagnosis through advanced machine learning algorithms. His academic activities combine theoretical AI research with practical healthcare applications, including lung cancer detection, brain tumor classification, cardiovascular disease prediction, maternal health risk assessment, and gastrointestinal image segmentation.[3]
Research Profile
- Research Assistant, Health Informatics Research Lab (HIRL)
- Research Fellow, Bangladesh Medical Research Council (BMRC)
- Research Assistant, ELITE Research Lab LLC, USA
- Research interests include AI, Medical Imaging, NLP, Computer Vision and Healthcare Analytics.
Research Contributions
His contributions include explainable deep learning models for lung cancer detection, uncertainty-aware brain tumor diagnosis, lightweight transformer-based polyp segmentation, cardiovascular disease prediction, maternal health analytics, Bangla handwriting recognition, and deployment of AI-enabled healthcare systems. His work integrates CNNs, Transformers, ensemble learning, Bayesian uncertainty estimation, and clinical feature engineering.[2]
Publications
- HALI-Net: Explainable Hybrid Deep Learning Model for Lung Cancer Detection (Intelligence-Based Medicine, 2026).
- Multiple journal submissions in Intelligence-Based Medicine, Array, and Engineering Reports.
- Conference papers published or accepted in IEEE, Springer Nature, and Atlantis Press proceedings.
- Creator of Bangla Handwritten Character and Word Recognition Dataset published on Zenodo.
Research Impact
Although at an early stage of his academic career, Mahmud has demonstrated substantial research productivity through first-author publications, corresponding authorship, competitive research fellowships, interdisciplinary collaborations, and practical AI applications addressing healthcare challenges. His work has potential relevance for clinical decision support, explainable diagnostics, and AI-assisted medical imaging.[4]
Award Suitability
Based on available academic evidence, Tamim Mahmud demonstrates characteristics commonly associated with emerging researcher recognition. These include strong first-author publication activity, participation in nationally funded research, leadership in AI-based healthcare projects, dataset development, and interdisciplinary collaboration. His research aligns well with awards recognizing innovation in artificial intelligence, medical informatics, and early-career scientific achievement.[4]
Conclusion
Tamim Mahmud represents a promising early-career researcher whose work integrates computer science with healthcare innovation. His growing publication record, involvement in funded research, and focus on explainable and clinically applicable AI demonstrate a commitment to advancing intelligent diagnostic technologies and medical decision-support systems.
External Links
References
- Curriculum Vitae of Tamim Mahmud (2026).
- Mahmud, T. (2026). HALI-Net: An Explainable Hybrid Deep Learning Model with Attention and Texture Fusion for Lung Cancer Detection in CT Images.
https://doi.org/10.1016/j.ibmed.2026.100419 - Mahmud, T. et al. Conference Proceedings (2025–2026), IEEE, Springer Nature, Atlantis Press.
- Google Scholar Profile.
https://scholar.google.com/citations?hl=en&user=THiIDGIAAAAJ